Load-based power adjustments for cellular communication sites

ABSTRACT

For a cluster of cellular communication sites, the power consumption and data load of each site is measured over multiple time periods to determine an energy factor indicating the degree by which the power consumption of each site increases with increasing data load. The energy factors are then analyzed to determine coverage area sizes for the communications sites that will serve a given area while taking advantage of more efficient site to reduce overall power consumption of the cluster of sites. Transmission power levels are then adjusted at the sites to achieve these coverage area sizes.

CROSS REFERENCE TO RELATED APPLICATIONS

This is a divisional application with claims priority to commonlyassigned, co-pending U.S. patent application Ser. No. 15/277,895, filedSep. 27, 2016. Application Ser. No. 15/277,895 is fully incorporatedherein by reference.

BACKGROUND

Energy costs can be significant for operators of cellular communicationsystems. Furthermore, the energy used by cellular radio sites of suchsystems can be a significant portion of total system energy usage.Management of radio site energy usage is therefore an important part ofensuring business health and revenue growth for cellular serviceproviders.

BRIEF DESCRIPTION OF THE DRAWINGS

The detailed description is described with reference to the accompanyingfigures. In the figures, the left-most digit(s) of a reference numberidentifies the figure in which the reference number first appears. Theuse of the same reference numbers in different figures indicates similaror identical components or features.

FIGS. 1A and 1B are representations of cellular communication sites andassociated coverage areas. FIG. 1A shows an initial configuration ofcoverage areas. FIG. 1B shows an updated or adjusted configuration ofthe coverage areas.

FIG. 2 is a flow diagram illustrating an example method of configuringcoverage areas of multiple cellular communication sites to reduceaggregate energy consumption of the sites.

FIG. 3 is a block diagram illustrating basic components of a cellularcommunication site and an associated energy monitoring components.

FIG. 4 is a block diagram of an example computing device that may beused to implement an energy monitoring component as described herein.

DETAILED DESCRIPTION

The described implementations provide devices, systems, and methods formanaging energy usage by cellular radio and radio-related components inan infrastructure having multiple cellular sites. In particular,techniques are introduced for determining the energy efficiencies ofmultiple cellular sites within a cluster of cellular sites havingpotentially overlapping coverage areas. The sites of the cluster arethen configured so that coverage areas of highly efficient cells areenlarged while the coverage areas of less efficient cells are reduced.

In a described embodiment, data throughput and energy usage aremonitored over multiple time periods for multiple cellular sites. Theenergy efficiencies of the sites are then calculated based on this data.More specifically, historical energy and throughput data are analyzed topredict the energy consumption of each site as a function of the datathroughput of the site.

Each site has a configurable coverage area. The coverage areas of thesites overlap each other to produce an aggregate coverage area. Inaccordance with embodiments described herein, the coverage areas of thesites are adjusted based on the energy efficiencies of the sites.Specifically, the coverage areas of sites having relatively highefficiencies are increased while the coverage areas of sites havingrelatively low efficiencies are decreased, while maintaining anapproximately unchanged aggregate coverage area.

FIG. 1A shows a portion of an example cellular communicationsinfrastructure 100. The infrastructure 100 includes a cluster of threecellular sites 102(a), 102(b), and 102(c), which for purposes ofillustration are represented as X's. Each site may comprise a basestation such as an eNodeB, as well as additional associated equipment.

Each site 102 has a corresponding coverage area or radius 104, indicatedas a dashed circle. Site 102(a) has a coverage area 104(a), site 102(b)has a coverage area 104(b), and site 102(c) has a coverage area 104(c).Initially, the sizes of the coverage areas 104 are all approximately thesame, producing an aggregate coverage area that includes the union ofthe coverage areas 104(a), 104(b), and 104(c).

As will be described in more detail below, energy analyses of thecellular sites 102 are performed to determine their energy consumptionsas functions of load. The coverage areas 104 are then adjusted in a waythat optimizes overall energy usage while maintaining approximately thesame size aggregate coverage area and data throughput capabilities.

FIG. 1B shows an example of adjusted coverage areas 104 of theinfrastructure 100, wherein the sizes of the coverage areas 104 areadjusted based on determined energy efficiencies of the respective cellsites 102. In the example, it is assumed that the site 102(a) has thebest or highest energy efficiency. Accordingly, the size of the coveragearea 104(a) of the site 102(a) has been increased. The site 102(b) hasthe worst or lowest energy efficiency and the size of its coverage area104(b) has accordingly been reduced. The site 102(c) has had the size ofits coverage area 104(c) slightly enlarged so that the three cell sitesmaintain the same aggregate coverage area. Note that the depiction ofthe coverage areas shown in FIGS. 1A and 1B may not accurately reflectthat the aggregate coverage area has remained approximately constant.

FIG. 2 illustrates an example method 200 for adjusting coverage areasfor a cluster of cell sites to improve overall energy efficiencies andto lower overall energy consumption. The method 200 is applied to acluster of two or more cell sites, and is based in part on an assumptionthat users and user data demands are uniformly distributed throughoutthe coverage areas of the cell sites. However, the method may be usedeven when this assumption is not strictly true.

For purposes of discussion, the site cluster is described as having nindividual sites C₀ through C_(n−1). Each site C_(i) has a coverage areahaving an initial or default coverage area size A₁(i). The coverage areaof a site is the area within which the site provides relatively reliablecommunications with user mobile devices, at data transfer rates thathave been deemed appropriate or adequate by the service provider. Thecoverage areas of the cluster potentially overlap each other, dependingon the geographical layout of the sites, to form an aggregate coveragearea having an initial coverage area size.

Cell site coverage area is typically represented as a circular areahaving a coverage radius r that is determined by the transmit powerlevels of the respective cellular sites or base stations. The coveragearea size is therefore considered equal to πr². The size of a particularcell site's coverage area can be varied by varying the transmit powerlevels of the radio equipment of the cell site, and/or by setting oradjusting various configuration parameters of the cell site equipmentthat have the effect of varying the transmit power.

An action 202 comprises monitoring energy consumption of the cellularcommunication sites of the cluster over multiple time periods. Forexample, energy consumption may be monitored for each of two consecutivemonths. The energy consumption for a particular cellular communicationsite i may be represented as power(i), as follows:

power(i)=energyConsumption(i)/(daysInMonth*totalSecondsinDay)   Equation(1)

An action 204 comprises monitoring the data load of each site i overmultiple time periods. Data load is a measure of data throughput ortransfer rate such as bits/second, number of current consuming users,etc. For example, the data load supported by each site may be monitoredfor each of two consecutive months, corresponding respectively to thesame two months for which energy consumption is monitored. The data loadmay be calculated as follows for a site i:

load(i)=totalTraffic(i)/(daysinMonth*totalSecondsinDay)   Equation (2)

where totalTraffic(i) represents the total amount of data transmittedand/or received during the monitored month to and/or from the siteC_(i).

An action 206 comprises analyzing (a) changes in the energy consumptionof each cellular communication site i and (b) corresponding changes inthe data load of each cellular communication site i to determine anenergy factor for each of the multiple cell sites of a cluster. Theenergy factor of a site indicates a degree by which the energyconsumption of the site changes in response to a change in the data loadof the site.

For a particular site i, energy consumption may be defined as follows:

power(i)=radioPower(i)+nonRadioPower(i)   Equation (3)

where power(i) is the average power used by the site i. The termradioPower(i) represents power that varies as a function of site dataloading, such as might be consumed by base band units (BBUs), remoteradio units (RRUs), etc. The term nonRadioPower(i) is a constant foreach site i and represents power that does not vary as a function ofsite data loading. Examples of components that contribute tonon-radio-power may include things such as power supplies, airconditioners/fans, feeder links, backhaul devices, monitoringcomponents, etc. Note that various components of a cell site may eachconsume a fixed amount of power as well as a variable amount of powerthat is dependent on load.

The variable power consumed by a site i, radioPower(i), can berepresented as follows:

radioPower(i)=f(i)×load(i)   Equation (4)

where load(i) is average data throughput as described above and f(i) isa factor, referred to herein as an energy factor, that is associatedwith each site i. As noted above, the energy factor f(i) indicates adegree by which the energy consumption of the site i changes in responseto a change in a data load of the site i.

Both power(i) and load(i) can be monitored over multiple time periods,such as monthly, and the monitored values can be used to solve for f(i).Given data for months j and k, the energy factor f(i) for a site i iscalculated as follows:

f(i)=[power(i,j)−power(i,k)]/[load(i,j)−load(i,k)]  Equation (5)

where power(i,j) is the measured power usage of site i for month j,power(i,k) is the measured power usage of site i for month k, load(i,j)is the measured load or data throughput of site i for month j, andload(i,k) is the measured load or data throughput of site i for month k.

For a cluster of cell sites C₀ through C_(n−1), the total variableamount of power consumption P_(RP), referred to herein as aggregateradio power, is calculated as follows:

$\begin{matrix}{P_{RP} = {\sum\limits_{i = 0}^{n - 1}\; {{f(i)} \times {{load}(i)}}}} & {{Equation}\mspace{14mu} (6)}\end{matrix}$

An action 208 comprises selecting adjusted coverage area sizes A₂(i) insuch a way that the aggregate energy consumption of the site cluster isreduced or minimized. In other words, the coverage area sizes areadjusted or selected so as to reduce or minimize a sum of a predictedenergy consumptions of the cellular communications sites, wherein theenergy consumptions are predicted by Equation (3) or Equation (4).

For purposes of analysis, it is assumed that the load of each cell isproportional to the adjusted coverage area size A₂(i) of the cell:load(i) ∝ A₂(i). Based on this assumption, the total power consumptionP_(RP) of the cluster of cells C₀ through C_(n−1) can be minimized byselecting the coverage area sizes A₂(0), A₂(1), . . . A₂(n−1) of therespective cell sites to minimize the following summation:

$\begin{matrix}{\sum\limits_{i = 0}^{n - 1}\; {{f(i)}*{A_{2}(i)}}} & {{Equation}\mspace{14mu} (7)}\end{matrix}$

subject to the constraints that (a) the total consumed energy P(i) foreach cell remains below its available maximum, dictated bycharacteristics of the cell site equipment, (b) the size of totalcoverage area remains unchanged after adjustment (i.e., an adjustedaggregate coverage area size Σ_(i=0) ^(n−1)A₂(i) is equal to theoriginal aggregate coverage area size Σ_(i=0) ^(n−1)A₁(i)), and (c) theaverage data throughput X(i) of each cell is equal or greater than adesired or predefined throughput X_(avg).

More generally, the total power consumption P_(RP) of the cluster ofcells C₀ through C_(n−1) can be minimized by selecting the coverageareas A₂(0), A₂(1), . . . A₂(n−1) of the respective cell sites tominimizing the following summation:

$\begin{matrix}{\sum\limits_{i = 0}^{n - 1}\; {{Func}\left( {{f(i)},{A_{2}(i)}} \right)}} & {{Equation}\mspace{14mu} (8)}\end{matrix}$

subject to the constraints enumerated above, where Func(f(i), A₂(i)) issome function of f(i) and A(i) that increases with an increasing energyfactor f(i) and with an increasing coverage area size A₂(i). In thedescribed embodiments, Func(f(i), A₂(i)) is the product of f(i) andA₂(i). Specifically, Func(f(i), A₂(i)) is f(i)*A₂(i)).

An action 210 comprises adjusting transmit power levels of the cellularcommunication sites based at least in part on the adjusted coverage areasizes. In the described embodiment, the action 210 comprises setting thetransmit power level of each cellular site to achieve a coverage radiusr(i) that results in the coverage area A₂(i), where A₂(i)=π*r(i)².

The average data throughput (capacity) of X(i) of a cell site i can becalculated as follows:

X(i)=B(i)*log₂(1+ξ)   Equation (9)

where B(i) is the channel bandwidth in Hertz of the cell site and ξ isthe signal-to-noise (SNR) interference ratio in a signal transmitted bythe cell site and received by a user device.

The SNR interference ratio ξ can be calculated as follows:

$\begin{matrix}{\xi = \frac{{P_{T,1}(r)}{h(r)}}{\sigma^{2} + {\Sigma \mspace{14mu} I_{k}}}} & {{Equation}\mspace{14mu} (10)}\end{matrix}$

where P_(T,1)(r) is the transmit power from the base station of the cellsite for a user at a distance r from the base station, σ² is the whitenoise level, I_(k) is the received inter-cell interference from a nearbycell site k, and h(r) is a distance factor that can be represented asfollows:

$\begin{matrix}{{h(r)} = \left( \frac{d_{0}}{r} \right)^{n}} & {{Equation}\mspace{14mu} (11)}\end{matrix}$

where d₀ is a close-in reference point in the far-field region of thetransmitter antenna and n is the path loss index.

The interference I_(k) can be represented as follows:

I _(k) =P _(k) *h(I _(k))   Equation (12)

where I_(k) is the distance from the base station of cell k to the user.

P _(k) is the average transmission power from cell k as follows:

$\begin{matrix}{{\overset{\_}{P}}_{k} = {\frac{1}{S_{k}}{\int{\int_{S_{k}}{{P_{T,k}(s)}{ds}}}}}} & {{Equation}\mspace{14mu} (13)}\end{matrix}$

where P_(T,k)(s) is the transmit power from base station k for the userswithin a unit small area ds, S_(k) is the total area size in cell kwhich can be approximately represented as π·r², and P_(k) is total powerconsumed to cover all users with the area, i.e., the integral value ofP_(T,k)(s) over S_(k).

FIG. 3 shows basic energy consumption components of an example cellularcommunication site 302, each of which may contribute to fixed powerconsumption of the site and/or to energy consumption that varies withdata load. Example components include one or more baseband units (BBUs)304; one or more remote radio units (RRUs) 306; air conditioning (AC) orother cooling equipment 308; one or more power supplies 310 that provideDC power to the BBUs 304, the RRUs 306, and other equipment; backhauldevices 312 that communicate with a radio network controller (RNC) 314and other external equipment; an antenna 316 that represents amplifiersand other equipment used in transmitting and receiving radio-frequencysignals to and from a user mobile device 318; and various monitoringequipment 320 such as energy usage meters, other meters, lights,operations, administration, and maintenance (OAM) devices, etc. Thevarious equipment receives power from a power utility 322.

In addition to these and other components of a cellular communicationsite, a system of multiple cellular communication sites may include oneor more energy monitoring components 324, such as one or more computersrunning various types of software that provide insights into energyconsumption and efficiencies of the multiple sites. In the contextdescribed herein, the energy monitoring components 324 may obtain or beprovided with energy usage and data load information and in response maycalculate optimized coverage areas for multiple clusters ofcommunication sites. Site technicians may be provided with the resultsof the optimizations. Specifically, the emerging monitoring components324 may provide a recommended coverage area or radius for each cellsite, which may be considered by technicians when setting transmissionpower levels of the site. In some cases, the energy monitoringcomponents 324 may directly control transmission power levels and mayaccordingly implement optimized transmission power levels without humaninvolvement.

FIG. 4 illustrates an example device 400 in accordance with variousembodiments. The device 400 is illustrative of an example energymonitoring component 324, and may therefore be configured to implementthe method 200.

In various embodiments, the computing device 400 may include at leastone processing unit 402 and system memory 404. Depending on theconfiguration and type of the computing device, the system memory 404may be volatile (such as RAM), non-volatile (such as ROM, flash memory,etc.) or some combination of the two. The system memory 404 may includean operating system 406, one or more program modules 408, and mayinclude program data 410.

The computing device 400 may also include additional data storagedevices (removable and/or non-removable) such as, for example, magneticdisks, optical disks, or tape. Such additional storage is illustrated inFIG. 4 by storage 412.

Non-transitory computer storage media of the computing device 400 mayinclude volatile and nonvolatile, removable and non-removable mediaimplemented in any method or technology for storage of information, suchas computer readable instructions, data structures, program modules, orother data. The system memory 404 and storage 412 are all examples ofcomputer-readable storage media. Non-transitory computer-readablestorage media includes, but is not limited to, RAM, ROM, EEPROM, flashmemory or other memory technology, CD-ROM, digital versatile disks (DVD)or other optical storage, magnetic cassettes, magnetic tape, magneticdisk storage or other magnetic storage devices, or any other mediumwhich can be used to store the desired information and which can beaccessed by computing device 400. Any such non-transitorycomputer-readable storage media may be part of the computing device 400.

In various embodiment, any or all of the system memory 404 and storage412 may store programming instructions that implement an executableprogram, which when executed by the processing unit 402 performs actionsimplementing some or all of the functionality described herein.

The computing device 400 may also have input device(s) 414 such as akeyboard, a mouse, a touch-sensitive display, voice input device, etc.Output device(s) 416 such as a display, speakers, a printer, etc. mayalso be included. The computing device 400 may also containcommunication connections 418 that allow the device to communicate withother computing devices 420.

Although features and/or methodological acts are described above, it isto be understood that the appended claims are not necessarily limited tothose features or acts. Rather, the features and acts described aboveare disclosed as example forms of implementing the claims.

What is claimed is:
 1. A method comprising: monitoring (a) energyconsumption and (b) data load of each cellular communication site i of acluster of n cellular communication sites, each cellular communicationsite i having a first coverage area and a corresponding first coveragearea size A1(i), wherein the first coverage areas of the cellularcommunication sites overlap to form a first aggregate coverage areahaving a first aggregate coverage area size; analyzing (a) changes inthe energy consumption of each cellular communication site i and (b)corresponding changes in the data load of each cellular communicationsite i to determine an energy factor f(i) of each cellular communicationsite i, wherein the energy factor of a particular cellular communicationsite indicates a degree by which the energy consumption of theparticular cellular communication site changes in response to a changein the data load of the particular cellular communication site;selecting second coverage area sizes A2(i) of each cellularcommunication site i so as to reduce Σ_(i=0) ^(n−1)Func(A₂(i), f(i)),where Func(A₂(i), f(i)) is a function of A₂(i) and f(i), the secondcoverage area sizes A2(i) corresponding to second coverage areas thatoverlap to form a second aggregate coverage area having a secondaggregate coverage area size that is approximately equal to the firstaggregate coverage area size; and adjusting transmit power levels of thecellular communication sites based at least in part on the selectedsecond coverage area sizes.
 2. The method of claim 1, wherein selectingthe second coverage area sizes is performed so that each cellular cell ihas at least an average data throughput.
 3. The method of claim 1, theanalyzing comprising: determining the energy consumption and the dataload for each cellular communication site of the cluster for a firsttime period j and a second time period k; calculating the energy factorf(i) of a particular cellular communication site i in accordance withthe following:f(i)=[power(i,j)−power(i,k)]/[load(i,j)−load(i,k)] where: power(i,j)represents energy consumed by the particular cellular communication sitei during the first time period; power(i,k) represents energy consumed bythe particular cellular communication site i during the second timeperiod; load(i,j) represents a data load of the particular cellularcommunication site i during the first time period; and load(i,k)represents a data load of the particular cellular communication site iduring the second time period.
 4. The method of claim 1, whereinselecting the second coverage area sizes is performed so as to minimizeΣ_(i=0) ^(n−1)Func(A₂(i), f(i)) while maintaining Σ_(i=0)^(n−1)A₂(i)≈Σ_(i=0) ^(n−1)A₁(i).
 5. The method of claim 1, whereinFunc(A₂(i), f(i)) comprises A₂(i)*f(i).
 6. The method of claim 1,wherein the coverage areas sizes correspond to respective coverage radiithat are determined by the transmit power levels of the respectivecellular communication sites.
 7. One or more non-transitory computerstorage media with a stored computer-executable program, which, whenexecuted by one or more processors of a first device, performs actionscomprising: analyzing energy consumption of a cluster of cellularcommunication sites to determine an energy factor for each of thecellular communication sites, the energy factor of a particular cellularcommunication site indicating a degree by which the energy consumptionof the particular cellular communication site changes in response to achange in a data load of the particular cellular communication site; andvarying a coverage area size of one or more of the cellularcommunication sites based at least in part on the energy factors of thecellular communication sites to reduce an aggregate energy consumptionof the cellular communication sites while maintaining (a) a givenaggregate coverage area of the cellular communication sites and (b) agiven average data throughput of the cellular communication sites. 8.The one or more non-transitory computer storage media of claim 7,wherein coverage area sizes of the cellular communication sitescorrespond to respective coverage radii that are determined by transmitpower levels of the respective cellular communication sites.
 9. The oneor more non-transitory computer storage media of claim 7, the actionsfurther comprising: calculating a predicted energy consumption of eachcellular communication site as a function of the energy factor of thecellular communication site and a data load of the cellularcommunication site; and selecting coverage area sizes of the cellularcommunication sites so as to reduce a sum of predicted energyconsumptions of the cellular communication sites.
 10. The one or morenon-transitory computer storage media of claim 7, wherein varying theone or more coverage area sizes is performed so as to to minimizeΣ_(i=0) ^(n)Func(A(i)*f(i)), where n is a number of cellularcommunication sites in the cluster, A(i) is a coverage area size of anindividual cellular communication site i of the cluster, f(i) is theenergy factor of the individual cellular communication site I, andFunc(A(i), f(i)) is a function of A(i) and f(i),
 11. The one or morenon-transitory computer storage media of claim 7, wherein varying theone or more coverage area sizes is performed so as to minimize Σ_(i=0)^(n)A(i)*f(i), where n is a number of cellular communication sites inthe cluster, A(i) is a coverage area size of an individual cellularcommunication site i of the cluster, and f(i) is the energy factor ofthe individual cellular communication site i.
 12. A system comprising: aprocessor; and programming instructions which, when executed by theprocessor, cause the system to perform operations including: monitoring(a) energy consumption and (b) data load of each cellular communicationsite i of a cluster of n cellular communication sites, each cellularcommunication site i having a first coverage area and a correspondingfirst coverage area size A1(i), wherein the first coverage areas of thecellular communication sites overlap to form a first aggregate coveragearea having a first aggregate coverage area size; analyzing (a) changesin the energy consumption of each cellular communication site i and (b)corresponding changes in the data load of each cellular communicationsite i to determine an energy factor f(i) of each cellular communicationsite i, wherein the energy factor of a particular cellular communicationsite indicates a degree by which the energy consumption of theparticular cellular communication site changes in response to a changein the data load of the particular cellular communication site;selecting second coverage area sizes A2(i) of each cellularcommunication site i so as to reduce Σ_(i=0) ^(n−1)Func(A₂(i), f(i)),where Func(A₂(i), f(i)) is a function of A₂(i) and f(i), the secondcoverage area sizes A2(i) corresponding to second coverage areas thatoverlap to form a second aggregate coverage area; and adjusting transmitpower levels of the cellular communication sites based at least in parton the selected second coverage area sizes.
 13. The system of claim 12,wherein selecting the second coverage area sizes is performed so thateach cellular cell i has at least an average data throughput.
 14. Thesystem of claim 12, wherein the operations further include: determiningthe energy consumption and the data load for each cellular communicationsite of the cluster for a first time period j and a second time periodk; calculating the energy factor f(i) of a particular cellularcommunication site i in accordance with the following:f(i)=[power(i,j)−power(i,k)]/[load(i,j)−load(i,k)] where: power(i,j)represents energy consumed by the particular cellular communication sitei during the first time period; power(i,k) represents energy consumed bythe particular cellular communication site i during the second timeperiod; load(i,j) represents a data load of the particular cellularcommunication site i during the first time period; and load(i,k)represents a data load of the particular cellular communication site iduring the second time period.
 15. The system of claim 12, whereinselecting the second coverage area sizes is performed so as to minimizeΣ_(i=0) ^(n−1)Func(A₂(i), f(i)) while maintaining Σ_(i=0) ^(n−1)A₂(i)≈Σ₀^(n−1)A₁(i).
 16. The system of claim 12, wherein Func(A₂(i), f(i))comprises A₂(i)*f(i).
 17. The system of claim 12, wherein the coverageareas sizes correspond to respective coverage radii that are determinedby the transmit power levels of the respective cellular communicationsites.
 18. The system of claim 12, wherein the second aggregate coveragearea having a second aggregate coverage area size that is approximatelyequal to the first aggregate coverage area size.
 19. The system of claim12, wherein the operations further include: predicting an energyconsumption as a function of data load; and varying a coverage area sizesetting of at least one of the cellular communication sites based atleast in part on the predicted energy consumption of the cellularcommunication sites to reduce an aggregate energy consumption of thecellular communication sites.
 20. The system of claim 19, wherein thecoverage area size setting of said at least one of the cellularcommunication sites corresponds to a coverage radius that is determinedby a transmit power level of said at least one of the cellularcommunication sites.